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SOCIAL NETWORK Michel Bruley WA - Marketing Director February 2012 Extract from various presentations: B Wellman, K Toyama, A Sharma, Teradata Aster,

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Page 1: SOCIAL NETWORK - Decideo•Walk > A sequence of actors and relations that begins and ends with actors •Geodesic distance > The number of relations in the shortest possible walk from

SOCIAL NETWORK

Michel Bruley

WA - Marketing Director

February 2012

Extract from various presentations: B Wellman, K Toyama, A Sharma, Teradata Aster, …

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2 2/2/2012 Teradata Confidential

Social Network

A social network is a

social structure between

actors, mostly individuals

or organizations

It indicates the ways in

which they are connected

through various social

familiarities, ranging

from casual acquaintance

to close familiar bonds

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3 2/2/2012 Teradata Confidential

Society as a Graph

People are represented as

nodes

Relationships are represented

as edges: relationships may be

acquaintanceship, friendship,

co-authorship, etc.

Allows analysis using tools of

mathematical graph theory

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4 2/2/2012 Teradata Confidential

Little Boxes Networked Individualism Glocalization

Social Network Analysis

Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers or other information/knowledge processing entities:

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Connections

• Size

> Number of nodes

• Density

> Number of ties that are present / the amount of ties that could be present

• Out-degree

> Sum of connections from an actor to others

• In-degree

> Sum of connections to an actor

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Distance

• Walk

> A sequence of actors and relations that begins and ends with actors

• Geodesic distance

> The number of relations in the shortest possible walk from one actor to another

• Maximum flow

> The amount of different actors in the neighborhood of a source that lead to pathways to a target

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Some Measures of Power & Prestige

• Degree

> Sum of connections from or to an actor

–Transitive weighted degreeAuthority, hub, pagerank

• Closeness centrality

> Distance of one actor to all others in the network

• Betweenness centrality

> Number that represents how frequently an actor is between other actors’ geodesic paths

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Cliques and Social Roles

• Cliques

> Sub-set of actors

More closely tied to each other than to actors who are not part of the sub-set:

•A lot of work on “trawling” for communities in the web-graph

•Often, you first find the clique (or a densely connected subgraph) and then try to interpret what the clique is about

• Social roles

> Defined by regularities in the patterns of relations among actors

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9 2/2/2012 Teradata Confidential

Network Analysis Example

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10 2/2/2012 Teradata Confidential

Centrality: strategic positions

Degree centrality:

Local attention

Beetweenness centrality:

reveal broker

"A place for good ideas"

Closeness centrality:

Capacity to communicate

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11 2/2/2012 Teradata Confidential

Social Network Analysis: what for?

• To control information flow

• To improve/stimulate communication

• To improve network resilience

• To trust

• Web applications of Social Networks examples: > Analyzing page importance (Page Rank,

Authorities/Hubs)

> Discovering Communities (Finding near-cliques)

> Analyzing Trust (Propagating Trust, Using propagated trust to fight spam - In Email or In Web page ranking)

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12 2/2/2012 Teradata Confidential

Tangible Outcomes from SNA

Sell More

Preserving Expertise Better Knowledge

Sharing

Building Better

Communities

More Innovation Competitive Intelligence

Organisational Re-structures

that work

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13 2/2/2012 Teradata Confidential

Challenges

• Large number of entities with rapidly growing amount of data for each

• Connectivity changing constantly

Aster Data Value

• SQL-MapReduce® function for Graph Analysis eases and accelerates analysis

• Ability to store and analyze massive volumes of data about users and connections

• High loading throughput and incremental loading to bring new data into analysis

Teradata Aster: See the Network

Understand connections among users and organizations

Examples

• Link analysis: predicting connections (among people, products, etc.) that are likely to be of interest by looking at known connections

• Influence analysis: identifying clusters and influencers in social networks

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Analysis of user behavior,

intent, and actions across

search, ad media and web

properties, in order to

drive increased ROI.

Teradata Aster References

Select Aster Data Customers in

Digital Marketing Optimization

Social Network & Relationship Analysis

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